Dynamic policy implementation for application-aware routing based on granular business insights

ABSTRACT

In one embodiment, a process captures one or more features of an initiated application transaction within an application, and applies the one or more features to one or more application-based policies. In response to determining a policy trigger for the initiated application transaction based on applying the one or more features to the one or more application-based policies, the process may then obtain a network address associated with the application. Once the process maps the particular policy trigger from the one or more application-based policies to one or more corresponding network-based policies, then the process can instruct a network controller to apply the one or more corresponding network-based policies to the network address associated with the application, causing the network controller to configure a computer network to manage network traffic associated with the network address according to the one or more corresponding network-based policies.

RELATED APPLICATION

This application claims priority to U.S. Provisional Application No.62/833,482, filed on Apr. 12, 2019, entitled DYNAMIC POLICYIMPLEMENTATION FOR APPLICATION-AWARE ROUTING BASED ON GRANULAR BUSINESSINSIGHTS, by Kunal Gupta, et al., the contents of which are incorporatedherein by reference.

TECHNICAL FIELD

The present disclosure relates generally to computer systems, and, moreparticularly, to dynamic policy implementation for application-awarerouting based on granular business insights.

BACKGROUND

The Internet and the World Wide Web have enabled the proliferation ofweb services available for virtually all types of businesses. Due to theaccompanying complexity of the infrastructure supporting the webservices, it is becoming increasingly difficult to maintain the highestlevel of service performance and user experience to keep up with theincrease in web services. For example, it can be challenging to piecetogether monitoring and logging data across disparate systems, tools,and layers in a network architecture. Moreover, even when data can beobtained, it is difficult to directly connect the chain of events andcause and effect.

In addition, software-defined wide area networks (SD-WANs) represent theapplication of software-defined networking (SDN) principles to WANconnections, such as connections to cellular networks, the Internet, andMultiprotocol Label Switching (MPLS) networks. The power of SD-WAN isthe ability to provide consistent service level agreement (SLA) forimportant application traffic transparently across various underlyingtunnels of varying transport quality and allow for seamless tunnelselection based on tunnel performance characteristics that can matchapplication SLAs.

In particular, with more and more workloads moving to the cloud,companies are looking at SD-WAN solutions to meet their applicationperformance needs. Currently, these SD-WAN solutions make intelligentrouting decisions by measuring and monitoring network performance overthe hybrid WAN. However, current SD-WAN networking decisions (e.g.,routing of packets, establishment of paths, etc.) lack application-basedbusiness context.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments herein may be better understood by referring to thefollowing description in conjunction with the accompanying drawings inwhich like reference numerals indicate identically or functionallysimilar elements, of which:

FIGS. 1A-1B illustrate an example computer network;

FIG. 2 illustrates an example computing device/node;

FIG. 3 illustrates an example application intelligence platform;

FIG. 4 illustrates an example system for implementing the exampleapplication intelligence platform;

FIG. 5 illustrates another example computing system for implementing thedisclosed technology;

FIG. 6 illustrates an example of a software-defined wide area network(SD-WAN) architecture for intent-based routing;

FIG. 7 illustrates an example system for dynamic policy implementationfor application-aware routing based on granular business insights;

FIG. 8 illustrates another example system for dynamic policyimplementation for application-aware routing based on granular businessinsights;

FIG. 9 illustrates an example of a process that may be used for dynamicpolicy implementation for application-aware routing based on granularbusiness insights;

FIGS. 10A-10B illustrate an example chart of channel utilization(standard and critical) based on dynamic policy implementation forapplication-aware routing based on granular business insights; and

FIG. 11 illustrates an example simplified procedure for dynamic policyimplementation for application-aware routing based on granular businessinsights.

DESCRIPTION OF EXAMPLE EMBODIMENTS Overview

According to one or more embodiments of the disclosure, techniquesherein provide for dynamic policy implementation for application-awarerouting based on granular business insights. In particular, in oneembodiment, a process captures one or more features of an initiatedapplication transaction within an application, and applies the one ormore features to one or more application-based policies. In response todetermining a policy trigger for the initiated application transactionbased on applying the one or more features to the one or moreapplication-based policies, the process may then obtain a networkaddress associated with the application. Once the process maps theparticular policy trigger from the one or more application-basedpolicies to one or more corresponding network-based policies, then theprocess can instruct a network controller to apply the one or morecorresponding network-based policies to the network address associatedwith the application, causing the network controller to configure acomputer network to manage network traffic associated with the networkaddress according to the one or more corresponding network-basedpolicies.

Other embodiments are described below, and this overview is not meant tolimit the scope of the present disclosure.

Description

A computer network is a geographically distributed collection of nodesinterconnected by communication links and segments for transporting databetween end nodes, such as personal computers and workstations, or otherdevices, such as sensors, etc. Many types of networks are available,ranging from local area networks (LANs) to wide area networks (WANs).LANs typically connect the nodes over dedicated private communicationslinks located in the same general physical location, such as a buildingor campus. WANs, on the other hand, typically connect geographicallydispersed nodes over long-distance communications links, such as commoncarrier telephone lines, optical lightpaths, synchronous opticalnetworks (SONET), synchronous digital hierarchy (SDH) links, orPowerline Communications (PLC), and others. The Internet is an exampleof a WAN that connects disparate networks throughout the world,providing global communication between nodes on various networks. Othertypes of networks, such as field area networks (FANs), neighborhood areanetworks (NANs), personal area networks (PANs), enterprise networks,etc. may also make up the components of any given computer network.

The nodes typically communicate over the network by exchanging discreteframes or packets of data according to predefined protocols, such as theTransmission Control Protocol/Internet Protocol (TCP/IP). In thiscontext, a protocol consists of a set of rules defining how the nodesinteract with each other. Computer networks may be furtherinterconnected by an intermediate network node, such as a router, toextend the effective “size” of each network.

Smart object networks, such as sensor networks, in particular, are aspecific type of network having spatially distributed autonomous devicessuch as sensors, actuators, etc., that cooperatively monitor physical orenvironmental conditions at different locations, such as, e.g.,energy/power consumption, resource consumption (e.g., water/gas/etc. foradvanced metering infrastructure or “AMI” applications) temperature,pressure, vibration, sound, radiation, motion, pollutants, etc. Othertypes of smart objects include actuators, e.g., responsible for turningon/off an engine or perform any other actions. Sensor networks, a typeof smart object network, are typically shared-media networks, such aswireless or power-line communication networks. That is, in addition toone or more sensors, each sensor device (node) in a sensor network maygenerally be equipped with a radio transceiver or other communicationport, a microcontroller, and an energy source, such as a battery.Generally, size and cost constraints on smart object nodes (e.g.,sensors) result in corresponding constraints on resources such asenergy, memory, computational speed and bandwidth.

FIG. 1A is a schematic block diagram of an example computer network 100illustratively comprising nodes/devices, such as a plurality ofrouters/devices interconnected by links or networks, as shown. Forexample, customer edge (CE) routers 110 may be interconnected withprovider edge (PE) routers 120 (e.g., PE-1, PE-2, and PE-3) in order tocommunicate across a core network, such as an illustrative networkbackbone 130. For example, routers 110, 120 may be interconnected by thepublic Internet, a multiprotocol label switching (MPLS) virtual privatenetwork (VPN), or the like. Data packets 140 (e.g., traffic/messages)may be exchanged among the nodes/devices of the computer network 100over links using predefined network communication protocols such as theTransmission Control Protocol/Internet Protocol (TCP/IP), User DatagramProtocol (UDP), Asynchronous Transfer Mode (ATM) protocol, Frame Relayprotocol, or any other suitable protocol. Those skilled in the art willunderstand that any number of nodes, devices, links, etc. may be used inthe computer network, and that the view shown herein is for simplicity.

In some implementations, a router or a set of routers may be connectedto a private network (e.g., dedicated leased lines, an optical network,etc.) or a virtual private network (VPN), such as an MPLS VPN thanks toa carrier network, via one or more links exhibiting very differentnetwork and service level agreement characteristics.

FIG. 1B illustrates an example of network 100 in greater detail,according to various embodiments. As shown, network backbone 130 mayprovide connectivity between devices located in different geographicalareas and/or different types of local networks. For example, network 100may comprise local/branch networks 160, 162 that include devices/nodes10-16 and devices/nodes 18-20, respectively, as well as a datacenter/cloud environment 150 that includes servers 152-154. Notably,local networks 160-162 and data center/cloud environment 150 may belocated in different geographic locations. Servers 152-154 may include,in various embodiments, any number of suitable servers or othercloud-based resources. As would be appreciated, network 100 may includeany number of local networks, data centers, cloud environments,devices/nodes, servers, etc.

In some embodiments, the techniques herein may be applied to othernetwork topologies and configurations. For example, the techniquesherein may be applied to peering points with high-speed links, datacenters, etc. Furthermore, in various embodiments, network 100 mayinclude one or more mesh networks, such as an Internet of Thingsnetwork. Loosely, the term “Internet of Things” or “IoT” refers touniquely identifiable objects (things) and their virtual representationsin a network-based architecture. In particular, the next frontier in theevolution of the Internet is the ability to connect more than justcomputers and communications devices, but rather the ability to connect“objects” in general, such as lights, appliances, vehicles, heating,ventilating, and air-conditioning (HVAC), windows and window shades andblinds, doors, locks, etc. The “Internet of Things” thus generallyrefers to the interconnection of objects (e.g., smart objects), such assensors and actuators, over a computer network (e.g., via IP), which maybe the public Internet or a private network.

Notably, shared-media mesh networks, such as wireless networks, areoften on what is referred to as Low-Power and Lossy Networks (LLNs),which are a class of network in which both the routers and theirinterconnect are constrained: LLN routers typically operate withconstraints, e.g., processing power, memory, and/or energy (battery),and their interconnects are characterized by, illustratively, high lossrates, low data rates, and/or instability. LLNs are comprised ofanything from a few dozen to thousands or even millions of LLN routers,and support point-to-point traffic (between devices inside the LLN),point-to-multipoint traffic (from a central control point such at theroot node to a subset of devices inside the LLN), andmultipoint-to-point traffic (from devices inside the LLN towards acentral control point). Often, an IoT network is implemented with anLLN-like architecture. For example, as shown, local network 160 may bean LLN in which CE-2 operates as a root node for nodes/devices 10-16 inthe local mesh, in some embodiments.

In still further embodiments, a software-defined WAN (SD-WAN) may beused in network 100, such as to connect local network 160, local network162, and data center/cloud 150. In general, an SD-WAN uses a softwaredefined networking (SDN)-based approach to instantiate tunnels on top ofthe physical network and control routing decisions, accordingly. Forexample, as noted above, one tunnel may connect CE-2 at the edge oflocal network 160 to CE-1 at the edge of data center/cloud 150 over anMPLS or Internet-based service provider network in backbone 130.Similarly, a second tunnel may also connect these routers over a4G/5G/LTE cellular service provider network. SD-WAN techniques allow theWAN functions to be virtualized, essentially forming a virtualconnection between local network 160 and data center/cloud 150 on top ofthe various underlying connections. Another feature of SD-WAN iscentralized management by a supervisory service that can monitor andadjust the various connections, as needed.

FIG. 2 is a schematic block diagram of an example computing device(e.g., apparatus) 200 that may be used with one or more embodimentsdescribed herein, e.g., as any of the devices shown in FIGS. 1A-1Babove, and particularly as specific devices as described further below.The device may comprise one or more network interfaces 210 (e.g., wired,wireless, etc.), at least one processor 220, and a memory 240interconnected by a system bus 250, as well as a power supply 260 (e.g.,battery, plug-in, etc.).

The network interface(s) 210 contain the mechanical, electrical, andsignaling circuitry for communicating data over links coupled to thenetwork 100, e.g., providing a data connection between device 200 andthe data network, such as the Internet. The network interfaces may beconfigured to transmit and/or receive data using a variety of differentcommunication protocols. For example, interfaces 210 may include wiredtransceivers, wireless transceivers, cellular transceivers, or the like,each to allow device 200 to communicate information to and from a remotecomputing device or server over an appropriate network. The same networkinterfaces 210 also allow communities of multiple devices 200 tointerconnect among themselves, either peer-to-peer, or up and down ahierarchy. Note, further, that the nodes may have two different types ofnetwork connections 210, e.g., wireless and wired/physical connections,and that the view herein is merely for illustration. Also, while thenetwork interface 210 is shown separately from power supply 260, fordevices using powerline communication (PLC) or Power over Ethernet(PoE), the network interface 210 may communicate through the powersupply 260, or may be an integral component of the power supply.

The memory 240 comprises a plurality of storage locations that areaddressable by the processor 220 and the network interfaces 210 forstoring software programs and data structures associated with theembodiments described herein. The processor 220 may comprise hardwareelements or hardware logic adapted to execute the software programs andmanipulate the data structures 245. An operating system 242, portions ofwhich are typically resident in memory 240 and executed by theprocessor, functionally organizes the device by, among other things,invoking operations in support of software processes and/or servicesexecuting on the device. These software processes and/or services maycomprise one or more functional processes 246, and on certain devices,an illustrative “Application-Aware Routing” Extension process 248, asdescribed herein. Notably, functional processes 246, when executed byprocessor(s) 220, cause each particular device 200 to perform thevarious functions corresponding to the particular device's purpose andgeneral configuration. For example, a router would be configured tooperate as a router, a server would be configured to operate as aserver, an access point (or gateway) would be configured to operate asan access point (or gateway), a client device would be configured tooperate as a client device, and so on.

It will be apparent to those skilled in the art that other processor andmemory types, including various computer-readable media, may be used tostore and execute program instructions pertaining to the techniquesdescribed herein. Also, while the description illustrates variousprocesses, it is expressly contemplated that various processes may beembodied as modules configured to operate in accordance with thetechniques herein (e.g., according to the functionality of a similarprocess). Further, while the processes have been shown separately, thoseskilled in the art will appreciate that processes may be routines ormodules within other processes.

—Application Intelligence Platform—

The embodiments herein relate to an application intelligence platformfor application performance management. In one aspect, as discussed withrespect to FIGS. 3-5 below, performance within a networking environmentmay be monitored, specifically by monitoring applications and entities(e.g., transactions, tiers, nodes, and machines) in the networkingenvironment using agents installed at individual machines at theentities. As an example, applications may be configured to run on one ormore machines (e.g., a customer will typically run one or more nodes ona machine, where an application consists of one or more tiers, and atier consists of one or more nodes). The agents collect data associatedwith the applications of interest and associated nodes and machineswhere the applications are being operated. Examples of the collecteddata may include performance data (e.g., metrics, metadata, etc.) andtopology data (e.g., indicating relationship information). Theagent-collected data may then be provided to one or more servers orcontrollers to analyze the data.

FIG. 3 is a block diagram of an example application intelligenceplatform 300 that can implement one or more aspects of the techniquesherein. The application intelligence platform is a system that monitorsand collects metrics of performance data for an application environmentbeing monitored. At the simplest structure, the application intelligenceplatform includes one or more agents 310 and one or moreservers/controllers 320. Note that while FIG. 3 shows four agents (e.g.,Agent 1 through Agent 4) communicatively linked to a single controller,the total number of agents and controllers can vary based on a number offactors including the number of applications monitored, how distributedthe application environment is, the level of monitoring desired, thelevel of user experience desired, and so on.

The controller 320 is the central processing and administration serverfor the application intelligence platform. The controller 320 serves abrowser-based user interface (UI) 330 that is the primary interface formonitoring, analyzing, and troubleshooting the monitored environment.The controller 320 can control and manage monitoring of businesstransactions (described below) distributed over application servers.Specifically, the controller 320 can receive runtime data from agents310 (and/or other coordinator devices), associate portions of businesstransaction data, communicate with agents to configure collection ofruntime data, and provide performance data and reporting through theinterface 330. The interface 330 may be viewed as a web-based interfaceviewable by a client device 340. In some implementations, a clientdevice 340 can directly communicate with controller 320 to view aninterface for monitoring data. The controller 320 can include avisualization system 350 for displaying the reports and dashboardsrelated to the disclosed technology. In some implementations, thevisualization system 350 can be implemented in a separate machine (e.g.,a server) different from the one hosting the controller 320.

Notably, in an illustrative Software as a Service (SaaS) implementation,a controller instance 320 may be hosted remotely by a provider of theapplication intelligence platform 300. In an illustrative on-premises(On-Prem) implementation, a controller instance 320 may be installedlocally and self-administered.

The controllers 320 receive data from different agents 310 (e.g., Agents1-4) deployed to monitor applications, databases and database servers,servers, and end user clients for the monitored environment. Any of theagents 310 can be implemented as different types of agents with specificmonitoring duties. For example, application agents may be installed oneach server that hosts applications to be monitored. Instrumenting anagent adds an application agent into the runtime process of theapplication.

Database agents, for example, may be software (e.g., a Java program)installed on a machine that has network access to the monitoreddatabases and the controller. Database agents query the monitoreddatabases in order to collect metrics and pass those metrics along fordisplay in a metric browser (e.g., for database monitoring and analysiswithin databases pages of the controller's UI 330). Multiple databaseagents can report to the same controller. Additional database agents canbe implemented as backup database agents to take over for the primarydatabase agents during a failure or planned machine downtime. Theadditional database agents can run on the same machine as the primaryagents or on different machines. A database agent can be deployed ineach distinct network of the monitored environment. Multiple databaseagents can run under different user accounts on the same machine.

Standalone machine agents, on the other hand, may be standalone programs(e.g., standalone Java programs) that collect hardware-relatedperformance statistics from the servers (or other suitable devices) inthe monitored environment. The standalone machine agents can be deployedon machines that host application servers, database servers, messagingservers, Web servers, etc. A standalone machine agent has an extensiblearchitecture (e.g., designed to accommodate changes).

End user monitoring (EUM) may be performed using browser agents andmobile agents to provide performance information from the point of viewof the client, such as a web browser or a mobile native application.Through EUM, web use, mobile use, or combinations thereof (e.g., by realusers or synthetic agents) can be monitored based on the monitoringneeds. Notably, browser agents (e.g., agents 310) can include Reportersthat report monitored data to the controller.

Monitoring through browser agents and mobile agents are generally unlikemonitoring through application agents, database agents, and standalonemachine agents that are on the server. In particular, browser agents maygenerally be embodied as small files using web-based technologies, suchas JavaScript agents injected into each instrumented web page (e.g., asclose to the top as possible) as the web page is served, and areconfigured to collect data. Once the web page has completed loading, thecollected data may be bundled into a beacon and sent to an EUMprocess/cloud for processing and made ready for retrieval by thecontroller. Browser real user monitoring (Browser RUM) provides insightsinto the performance of a web application from the point of view of areal or synthetic end user. For example, Browser RUM can determine howspecific Ajax or iframe calls are slowing down page load time and howserver performance impact end user experience in aggregate or inindividual cases.

A mobile agent, on the other hand, may be a small piece of highlyperformant code that gets added to the source of the mobile application.Mobile RUM provides information on the native mobile application (e.g.,iOS or Android applications) as the end users actually use the mobileapplication. Mobile RUM provides visibility into the functioning of themobile application itself and the mobile application's interaction withthe network used and any server-side applications with which the mobileapplication communicates.

Application Intelligence Monitoring: The disclosed technology canprovide application intelligence data by monitoring an applicationenvironment that includes various services such as web applicationsserved from an application server (e.g., Java virtual machine (JVM),Internet Information Services (IIS), Hypertext Preprocessor (PHP) Webserver, etc.), databases or other data stores, and remote services suchas message queues and caches. The services in the applicationenvironment can interact in various ways to provide a set of cohesiveuser interactions with the application, such as a set of user servicesapplicable to end user customers.

Application Intelligence Modeling: Entities in the applicationenvironment (such as the JBoss service, MQSeries modules, and databases)and the services provided by the entities (such as a login transaction,service or product search, or purchase transaction) may be mapped to anapplication intelligence model. In the application intelligence model, abusiness transaction represents a particular service provided by themonitored environment. For example, in an e-commerce application,particular real-world services can include a user logging in, searchingfor items, or adding items to the cart. In a content portal, particularreal-world services can include user requests for content such assports, business, or entertainment news. In a stock trading application,particular real-world services can include operations such as receivinga stock quote, buying, or selling stocks.

Business Transactions: A business transaction representation of theparticular service provided by the monitored environment provides a viewon performance data in the context of the various tiers that participatein processing a particular request. A business transaction, which mayeach be identified by a unique business transaction identification (ID),represents the end-to-end processing path used to fulfill a servicerequest in the monitored environment (e.g., adding items to a shoppingcart, storing information in a database, purchasing an item online,etc.). Thus, a business transaction is a type of user-initiated actionin the monitored environment defined by an entry point and a processingpath across application servers, databases, and potentially many otherinfrastructure components. Each instance of a business transaction is anexecution of that transaction in response to a particular user request(e.g., a socket call, illustratively associated with the TCP layer). Abusiness transaction can be created by detecting incoming requests at anentry point and tracking the activity associated with request at theoriginating tier and across distributed components in the applicationenvironment (e.g., associating the business transaction with a 4-tupleof a source IP address, source port, destination IP address, anddestination port). A flow map can be generated for a businesstransaction that shows the touch points for the business transaction inthe application environment. In one embodiment, a specific tag may beadded to packets by application specific agents for identifying businesstransactions (e.g., a custom header field attached to a hypertexttransfer protocol (HTTP) payload by an application agent, or by anetwork agent when an application makes a remote socket call), such thatpackets can be examined by network agents to identify the businesstransaction identifier (ID) (e.g., a Globally Unique Identifier (GUID)or Universally Unique Identifier (UUID)).

Performance monitoring can be oriented by business transaction to focuson the performance of the services in the application environment fromthe perspective of end users. Performance monitoring based on businesstransactions can provide information on whether a service is available(e.g., users can log in, check out, or view their data), response timesfor users, and the cause of problems when the problems occur.

A business application is the top-level container in the applicationintelligence model. A business application contains a set of relatedservices and business transactions. In some implementations, a singlebusiness application may be needed to model the environment. In someimplementations, the application intelligence model of the applicationenvironment can be divided into several business applications. Businessapplications can be organized differently based on the specifics of theapplication environment. One consideration is to organize the businessapplications in a way that reflects work teams in a particularorganization, since role-based access controls in the Controller UI areoriented by business application.

A node in the application intelligence model corresponds to a monitoredserver or JVM in the application environment. A node is the smallestunit of the modeled environment. In general, a node corresponds to anindividual application server, JVM, or Common Language Runtime (CLR) onwhich a monitoring Agent is installed. Each node identifies itself inthe application intelligence model. The Agent installed at the node isconfigured to specify the name of the node, tier, and businessapplication under which the Agent reports data to the Controller.

Business applications contain tiers, the unit in the applicationintelligence model that includes one or more nodes. Each node representsan instrumented service (such as a web application). While a node can bea distinct application in the application environment, in theapplication intelligence model, a node is a member of a tier, which,along with possibly many other tiers, make up the overall logicalbusiness application.

Tiers can be organized in the application intelligence model dependingon a mental model of the monitored application environment. For example,identical nodes can be grouped into a single tier (such as a cluster ofredundant servers). In some implementations, any set of nodes, identicalor not, can be grouped for the purpose of treating certain performancemetrics as a unit into a single tier.

The traffic in a business application flows among tiers and can bevisualized in a flow map using lines among tiers. In addition, the linesindicating the traffic flows among tiers can be annotated withperformance metrics. In the application intelligence model, there maynot be any interaction among nodes within a single tier. Also, in someimplementations, an application agent node cannot belong to more thanone tier. Similarly, a machine agent cannot belong to more than onetier. However, more than one machine agent can be installed on amachine.

A backend is a component that participates in the processing of abusiness transaction instance. A backend is not instrumented by anagent. A backend may be a web server, database, message queue, or othertype of service. The agent recognizes calls to these backend servicesfrom instrumented code (called exit calls). When a service is notinstrumented and cannot continue the transaction context of the call,the agent determines that the service is a backend component. The agentpicks up the transaction context at the response at the backend andcontinues to follow the context of the transaction from there.

Performance information is available for the backend call. For detailedtransaction analysis for the leg of a transaction processed by thebackend, the database, web service, or other application need to beinstrumented.

The application intelligence platform uses both self-learned baselinesand configurable thresholds to help identify application issues. Acomplex distributed application has a large number of performancemetrics and each metric is important in one or more contexts. In suchenvironments, it is difficult to determine the values or ranges that arenormal for a particular metric; set meaningful thresholds on which tobase and receive relevant alerts; and determine what is a “normal”metric when the application or infrastructure undergoes change. Forthese reasons, the disclosed application intelligence platform canperform anomaly detection based on dynamic baselines or thresholds.

The disclosed application intelligence platform automatically calculatesdynamic baselines for the monitored metrics, defining what is “normal”for each metric based on actual usage. The application intelligenceplatform uses these baselines to identify subsequent metrics whosevalues fall out of this normal range. Static thresholds that are tediousto set up and, in rapidly changing application environments,error-prone, are no longer needed.

The disclosed application intelligence platform can use configurablethresholds to maintain service level agreements (SLAs) and ensureoptimum performance levels for system by detecting slow, very slow, andstalled transactions. Configurable thresholds provide a flexible way toassociate the right business context with a slow request to isolate theroot cause.

In addition, health rules can be set up with conditions that use thedynamically generated baselines to trigger alerts or initiate othertypes of remedial actions when performance problems are occurring or maybe about to occur.

For example, dynamic baselines can be used to automatically establishwhat is considered normal behavior for a particular application.Policies and health rules can be used against baselines or other healthindicators for a particular application to detect and troubleshootproblems before users are affected. Health rules can be used to definemetric conditions to monitor, such as when the “average response time isfour times slower than the baseline”. The health rules can be createdand modified based on the monitored application environment.

Examples of health rules for testing business transaction performancecan include business transaction response time and business transactionerror rate. For example, health rule that tests whether the businesstransaction response time is much higher than normal can define acritical condition as the combination of an average response timegreater than the default baseline by 3 standard deviations and a loadgreater than 50 calls per minute. In some implementations, this healthrule can define a warning condition as the combination of an averageresponse time greater than the default baseline by 2 standard deviationsand a load greater than 100 calls per minute. In some implementations,the health rule that tests whether the business transaction error rateis much higher than normal can define a critical condition as thecombination of an error rate greater than the default baseline by 3standard deviations and an error rate greater than 10 errors per minuteand a load greater than 50 calls per minute. In some implementations,this health rule can define a warning condition as the combination of anerror rate greater than the default baseline by 2 standard deviationsand an error rate greater than 5 errors per minute and a load greaterthan 50 calls per minute. These are non-exhaustive and non-limitingexamples of health rules and other health rules can be defined asdesired by the user.

Policies can be configured to trigger actions when a health rule isviolated or when any event occurs. Triggered actions can includenotifications, diagnostic actions, auto-scaling capacity, runningremediation scripts.

Most of the metrics relate to the overall performance of the applicationor business transaction (e.g., load, average response time, error rate,etc.) or of the application server infrastructure (e.g., percentage CPUbusy, percentage of memory used, etc.). The Metric Browser in thecontroller UI can be used to view all of the metrics that the agentsreport to the controller.

In addition, special metrics called information points can be created toreport on how a given business (as opposed to a given application) isperforming. For example, the performance of the total revenue for acertain product or set of products can be monitored. Also, informationpoints can be used to report on how a given code is performing, forexample how many times a specific method is called and how long it istaking to execute. Moreover, extensions that use the machine agent canbe created to report user defined custom metrics. These custom metricsare base-lined and reported in the controller, just like the built-inmetrics.

All metrics can be accessed programmatically using a RepresentationalState Transfer (REST) API that returns either the JavaScript ObjectNotation (JSON) or the eXtensible Markup Language (XML) format. Also,the REST API can be used to query and manipulate the applicationenvironment.

Snapshots provide a detailed picture of a given application at a certainpoint in time. Snapshots usually include call graphs that allow thatenables drilling down to the line of code that may be causingperformance problems. The most common snapshots are transactionsnapshots.

FIG. 4 illustrates an example application intelligence platform (system)400 for performing one or more aspects of the techniques herein. Thesystem 400 in FIG. 4 includes client device 405 and 492, mobile device415, network 420, network server 425, application servers 430, 440, 450,and 460, asynchronous network machine 470, data stores 480 and 485,controller 490, and data collection server 495. The controller 490 caninclude visualization system 496 for providing displaying of the reportgenerated for performing the field name recommendations for fieldextraction as disclosed in the present disclosure. In someimplementations, the visualization system 496 can be implemented in aseparate machine (e.g., a server) different from the one hosting thecontroller 490.

Client device 405 may include network browser 410 and be implemented asa computing device, such as for example a laptop, desktop, workstation,or some other computing device. Network browser 410 may be a clientapplication for viewing content provided by an application server, suchas application server 430 via network server 425 over network 420.

Network browser 410 may include agent 412. Agent 412 may be installed onnetwork browser 410 and/or client 405 as a network browser add-on,downloading the application to the server, or in some other manner.Agent 412 may be executed to monitor network browser 410, the operatingsystem of client 405, and any other application, API, or anothercomponent of client 405. Agent 412 may determine network browsernavigation timing metrics, access browser cookies, monitor code, andtransmit data to data collection 495, controller 490, or another device.Agent 412 may perform other operations related to monitoring a requestor a network at client 405 as discussed herein including reportgenerating.

Mobile device 415 is connected to network 420 and may be implemented asa portable device suitable for sending and receiving content over anetwork, such as for example a mobile phone, smart phone, tabletcomputer, or other portable device. Both client device 405 and mobiledevice 415 may include hardware and/or software configured to access aweb service provided by network server 425.

Mobile device 415 may include network browser 417 and an agent 419.Mobile device may also include client applications and other code thatmay be monitored by agent 419. Agent 419 may reside in and/orcommunicate with network browser 417, as well as communicate with otherapplications, an operating system, APIs and other hardware and softwareon mobile device 415. Agent 419 may have similar functionality as thatdescribed herein for agent 412 on client 405, and may report data todata collection server 495 and/or controller 490.

Network 420 may facilitate communication of data among differentservers, devices and machines of system 400 (some connections shown withlines to network 420, some not shown). The network may be implemented asa private network, public network, intranet, the Internet, a cellularnetwork, Wi-Fi network, VoIP network, or a combination of one or more ofthese networks. The network 420 may include one or more machines such asload balance machines and other machines.

Network server 425 is connected to network 420 and may receive andprocess requests received over network 420. Network server 425 may beimplemented as one or more servers implementing a network service, andmay be implemented on the same machine as application server 430 or oneor more separate machines. When network 420 is the Internet, networkserver 425 may be implemented as a web server.

Application server 430 communicates with network server 425, applicationservers 440 and 450, and controller 490. Application server 450 may alsocommunicate with other machines and devices (not illustrated in FIG. 4).Application server 430 may host an application or portions of adistributed application. The host application 432 may be in one of manyplatforms, such as including a Java, PHP, .Net, and Node.JS, beimplemented as a Java virtual machine, or include some other host type.Application server 430 may also include one or more agents 434 (i.e.,“modules”), including a language agent, machine agent, and networkagent, and other software modules. Application server 430 may beimplemented as one server or multiple servers as illustrated in FIG. 4.

Application 432 and other software on application server 430 may beinstrumented using byte code insertion, or byte code instrumentation(BCI), to modify the object code of the application or other software.The instrumented object code may include code used to detect callsreceived by application 432, calls sent by application 432, andcommunicate with agent 434 during execution of the application. BCI mayalso be used to monitor one or more sockets of the application and/orapplication server in order to monitor the socket and capture packetscoming over the socket.

In some embodiments, server 430 may include applications and/or codeother than a virtual machine. For example, servers 430, 440, 450, and460 may each include Java code, .Net code, PHP code, Ruby code, C code,C++ or other binary code to implement applications and process requestsreceived from a remote source. References to a virtual machine withrespect to an application server are intended to be for exemplarypurposes only.

Agents 434 on application server 430 may be installed, downloaded,embedded, or otherwise provided on application server 430. For example,agents 434 may be provided in server 430 by instrumentation of objectcode, downloading the agents to the server, or in some other manner.Agent 434 may be executed to monitor application server 430, monitorcode running in a virtual machine 432 (or other program language, suchas a PHP, .Net, or C program), machine resources, network layer data,and communicate with byte instrumented code on application server 430and one or more applications on application server 430.

Each of agents 434, 444, 454, and 464 may include one or more agents,such as language agents, machine agents, and network agents. A languageagent may be a type of agent that is suitable to run on a particularhost. Examples of language agents include a Java agent, .Net agent, PHPagent, and other agents. The machine agent may collect data from aparticular machine on which it is installed. A network agent may capturenetwork information, such as data collected from a socket.

Agent 434 may detect operations such as receiving calls and sendingrequests by application server 430, resource usage, and incomingpackets. Agent 434 may receive data, process the data, for example byaggregating data into metrics, and transmit the data and/or metrics tocontroller 490. Agent 434 may perform other operations related tomonitoring applications and application server 430 as discussed herein.For example, agent 434 may identify other applications, share businesstransaction data, aggregate detected runtime data, and other operations.

An agent may operate to monitor a node, tier of nodes, or other entity.A node may be a software program or a hardware component (e.g., memory,processor, and so on). A tier of nodes may include a plurality of nodeswhich may process a similar business transaction, may be located on thesame server, may be associated with each other in some other way, or maynot be associated with each other.

A language agent may be an agent suitable to instrument or modify,collect data from, and reside on a host. The host may be a Java, PHP,.Net, Node.JS, or other type of platform. Language agents may collectflow data as well as data associated with the execution of a particularapplication. The language agent may instrument the lowest level of theapplication to gather the flow data. The flow data may indicate whichtier is communicating with which tier and on which port. In someinstances, the flow data collected from the language agent includes asource IP, a source port, a destination IP, and a destination port. Thelanguage agent may report the application data and call chain data to acontroller. The language agent may report the collected flow dataassociated with a particular application to a network agent.

A network agent may be a standalone agent that resides on the host andcollects network flow group data. The network flow group data mayinclude a source IP, destination port, destination IP, and protocolinformation for network flow received by an application on which networkagent is installed. The network agent may collect data by interceptingand performing packet capture on packets coming in from one or morenetwork interfaces (e.g., so that data generated/received by all theapplications using sockets can be intercepted). The network agent mayreceive flow data from a language agent that is associated withapplications to be monitored. For flows in the flow group data thatmatch flow data provided by the language agent, the network agent rollsup the flow data to determine metrics such as TCP throughput, TCP loss,latency, and bandwidth. The network agent may then report the metrics,flow group data, and call chain data to a controller. The network agentmay also make system calls at an application server to determine systeminformation, such as for example a host status check, a network statuscheck, socket status, and other information.

A machine agent, which may be referred to as an infrastructure agent,may reside on the host and collect information regarding the machinewhich implements the host. A machine agent may collect and generatemetrics from information such as processor usage, memory usage, andother hardware information.

Each of the language agent, network agent, and machine agent may reportdata to the controller. Controller 490 may be implemented as a remoteserver that communicates with agents located on one or more servers ormachines. The controller may receive metrics, call chain data and otherdata, correlate the received data as part of a distributed transaction,and report the correlated data in the context of a distributedapplication implemented by one or more monitored applications andoccurring over one or more monitored networks. The controller mayprovide reports, one or more user interfaces, and other information fora user.

Agent 434 may create a request identifier for a request received byserver 430 (for example, a request received by a client 405 or 415associated with a user or another source). The request identifier may besent to client 405 or mobile device 415, whichever device sent therequest. In embodiments, the request identifier may be created when datais collected and analyzed for a particular business transaction.

Each of application servers 440, 450, and 460 may include an applicationand agents. Each application may run on the corresponding applicationserver. Each of applications 442, 452, and 462 on application servers440-460 may operate similarly to application 432 and perform at least aportion of a distributed business transaction. Agents 444, 454, and 464may monitor applications 442-462, collect and process data at runtime,and communicate with controller 490. The applications 432, 442, 452, and462 may communicate with each other as part of performing a distributedtransaction. Each application may call any application or method ofanother virtual machine.

Asynchronous network machine 470 may engage in asynchronouscommunications with one or more application servers, such as applicationserver 450 and 460. For example, application server 450 may transmitseveral calls or messages to an asynchronous network machine. Ratherthan communicate back to application server 450, the asynchronousnetwork machine may process the messages and eventually provide aresponse, such as a processed message, to application server 460.Because there is no return message from the asynchronous network machineto application server 450, the communications among them areasynchronous.

Data stores 480 and 485 may each be accessed by application servers suchas application server 460. Data store 485 may also be accessed byapplication server 450. Each of data stores 480 and 485 may store data,process data, and return queries received from an application server.Each of data stores 480 and 485 may or may not include an agent.

Controller 490 may control and manage monitoring of businesstransactions distributed over application servers 430-460. In someembodiments, controller 490 may receive application data, including dataassociated with monitoring client requests at client 405 and mobiledevice 415, from data collection server 495. In some embodiments,controller 490 may receive application monitoring data and network datafrom each of agents 412, 419, 434, 444, and 454 (also referred to hereinas “application monitoring agents”). Controller 490 may associateportions of business transaction data, communicate with agents toconfigure collection of data, and provide performance data and reportingthrough an interface. The interface may be viewed as a web-basedinterface viewable by client device 492, which may be a mobile device,client device, or any other platform for viewing an interface providedby controller 490. In some embodiments, a client device 492 may directlycommunicate with controller 490 to view an interface for monitoringdata.

Client device 492 may include any computing device, including a mobiledevice or a client computer such as a desktop, work station or othercomputing device. Client computer 492 may communicate with controller490 to create and view a custom interface. In some embodiments,controller 490 provides an interface for creating and viewing the custominterface as a content page, e.g., a web page, which may be provided toand rendered through a network browser application on client device 492.

Applications 432, 442, 452, and 462 may be any of several types ofapplications. Examples of applications that may implement applications432-462 include a Java, PHP, .Net, Node.JS, and other applications.

FIG. 5 is a block diagram of a computer system 500 for implementing thepresent technology, which is a specific implementation of device 200 ofFIG. 2 above. System 500 of FIG. 5 may be implemented in the contexts ofthe likes of clients 405, 492, network server 425, servers 430, 440,450, 460, asynchronous network machine 470, and controller 490 of FIG.4. (Note that the specifically configured system 500 of FIG. 5 and thecustomized device 200 of FIG. 2 are not meant to be mutually exclusive,and the techniques herein may be performed by any suitably configuredcomputing device.)

The computing system 500 of FIG. 5 includes one or more processors 510and memory 520. Main memory 520 stores, in part, instructions and datafor execution by processor 510. Main memory 520 can store the executablecode when in operation. The system 500 of FIG. 5 further includes a massstorage device 530, portable storage medium drive(s) 540, output devices550, user input devices 560, a graphics display 570, and peripheraldevices 580.

The components shown in FIG. 5 are depicted as being connected via asingle bus 590. However, the components may be connected through one ormore data transport means. For example, processor unit 510 and mainmemory 520 may be connected via a local microprocessor bus, and the massstorage device 530, peripheral device(s) 580, portable or remote storagedevice 540, and display system 570 may be connected via one or moreinput/output (I/O) buses.

Mass storage device 530, which may be implemented with a magnetic diskdrive or an optical disk drive, is a non-volatile storage device forstoring data and instructions for use by processor unit 510. Massstorage device 530 can store the system software for implementingembodiments of the present disclosure for purposes of loading thatsoftware into main memory 520.

Portable storage device 540 operates in conjunction with a portablenon-volatile storage medium, such as a compact disk, digital video disk,magnetic disk, flash storage, etc. to input and output data and code toand from the computer system 500 of FIG. 5. The system software forimplementing embodiments of the present disclosure may be stored on sucha portable medium and input to the computer system 500 via the portablestorage device 540.

Input devices 560 provide a portion of a user interface. Input devices560 may include an alpha-numeric keypad, such as a keyboard, forinputting alpha-numeric and other information, or a pointing device,such as a mouse, a trackball, stylus, or cursor direction keys.Additionally, the system 500 as shown in FIG. 5 includes output devices550. Examples of suitable output devices include speakers, printers,network interfaces, and monitors.

Display system 570 may include a liquid crystal display (LCD) or othersuitable display device. Display system 570 receives textual andgraphical information, and processes the information for output to thedisplay device.

Peripherals 580 may include any type of computer support device to addadditional functionality to the computer system. For example, peripheraldevice(s) 580 may include a modem or a router.

The components contained in the computer system 500 of FIG. 5 caninclude a personal computer, hand held computing device, telephone,mobile computing device, workstation, server, minicomputer, mainframecomputer, or any other computing device. The computer can also includedifferent bus configurations, networked platforms, multi-processorplatforms, etc. Various operating systems can be used including Unix,Linux, Windows, Apple OS, and other suitable operating systems,including mobile versions.

When implementing a mobile device such as smart phone or tabletcomputer, the computer system 500 of FIG. 5 may include one or moreantennas, radios, and other circuitry for communicating over wirelesssignals, such as for example communication using Wi-Fi, cellular, orother wireless signals.

—Dynamic Policy Implementation for Application-Aware Routing based onGranular Business Insights—

As mentioned above, software-defined wide area networks (SD-WANs)represent the application of software-defined networking (SDN)principles to WAN connections, such as connections to cellular networks,the Internet, and Multiprotocol Label Switching (MPLS) networks. Thepower of SD-WAN is the ability to provide consistent service levelagreement (SLA) for important application traffic transparently acrossvarious underlying tunnels of varying transport quality and allow forseamless tunnel selection based on tunnel performance characteristicsthat can match application SLAs.

In particular, with more and more workloads moving to the cloud,companies are looking at SD-WAN solutions to meet their applicationperformance needs. Currently, these SD-WAN solutions make intelligentrouting decisions by measuring and monitoring network performance overthe hybrid WAN. However, current SD-WAN networking decisions (e.g.,routing of packets, establishment of paths, etc.) lack application-basedbusiness context, which is important for enterprise architectureslooking to SD-WAN solutions for optimal application performance. Forinstance, though current techniques gather some basic applicationinsights from the application traffic flowing through the WAN, such asapplication type, class, etc., these solutions are not truly businessaware/intelligent as they lack the depth and granularity of a company'sbusiness context and business needs.

As an example, assume an environment where a hospital enterprise has anumber of hospital worksites with branch networks that may be connectedto a central data center and a public cloud. At each hospital there mayalso be a plurality of kiosks for doctors and nurses to manage patientson a given application. Traditionally, network traffic related to thegiven application to and/or from the data center would all be routed ina similar manner (e.g., the same as any other network communication, orelse with all traffic for the application being treated at a higherlevel of service). Now assume, however, that the hospital wishes totreat network traffic of the application for critical patientsdifferently than non-critical patients (e.g., treating critical careapplications with higher priority, lower latency, etc. than routine careapplications). Current policies and SD-WAN management techniques do notprovide such granularity, neither in terms of application visibility norunderlying network control.

The techniques herein, therefore, provide for an advanced level ofintegration between application monitoring and awareness and SD-WANmanagement, whereby the techniques, described in greater detail below,are able to capture a company's critical business need using theapplication intelligence platform above, and can then apply networkpolicies in an SD-WAN on-the-fly to provide a better applicationexperience for users.

Specifically, according to one or more embodiments described herein, aprocess (e.g., application intelligence platform's application awarerouting process 248) captures one or more features of an initiatedapplication transaction within an application, and applies the one ormore features to one or more application-based policies. In response todetermining a policy trigger for the initiated application transactionbased on applying the one or more features to the one or moreapplication-based policies, the process may then obtain a networkaddress associated with the application. Once the process maps theparticular policy trigger from the one or more application-basedpolicies to one or more corresponding network-based policies, then theprocess can instruct a network controller (e.g., SD-WAN controller) toapply the one or more corresponding network-based policies to thenetwork address associated with the application, causing the networkcontroller to configure a computer network to manage network trafficassociated with the network address according to the one or morecorresponding network-based policies.

Operationally, and as described further below, an “Application-AwareRouting” Extension (e.g., process 248) is built that can capturebusiness intelligence/application features from applications (e.g.,Business Transactions and other related information), obtain an IPaddress associated with the application associated with a given feature(e.g., a particular BT), and can assist in applying network policiesbased on the IP address (and thus based on the granular applicationfeature) on-demand, such as through integration with an SD-WANmanagement system. In particular, IP address records are extracted froman “Events Service” (e.g., from their string value to an IP addressreadable by the SD-WAN routing processes). Also, in order to create apolicy or health rule that might be used to trigger an HTTP request(e.g., to a third party REST API), a numeric metric may be needed forthe criteria of the health rule. Furthermore, the techniques hereintrack the IP addresses (e.g., by the extension process 248) so that noduplicate instructions are sent to the third party REST API (whichrequires logic that goes beyond currently available capabilities).

Notably, web pages (and/or applications) may be monitored using varioustypes of Browser Real User Monitoring (BRUM) products or alternativelyEnd User Monitoring (EUM) products (e.g., agents, as described above),which report performance data about the page and its resources, such asJavaScripts (JS), Stylesheets (CSS), images, etc. In particular, JavaScript Agents (“JSAgents”), as mentioned above, may be configured tocollect and reports performance data about web pages and theirresources, such as JS, CSS, images, etc.

FIG. 6 illustrates an example of an SD-WAN architecture 600 (e.g., forintent-based routing), wherein various branches 620 of an enterprise maybe connected to a data center 630 and public internet/cloud 610 (e.g.,with apps 612, servers 614, etc.) through various network connections640, such as MPLS 642, 4G LTE 644, Broadband 646, and so on.

The techniques herein bridge application intelligence with SD-WANmanagement such that the underlying network policies can be driven bybusiness policies. By using the application intelligence platformdescribed above, the techniques herein can capture the true businessintent by capturing a business transaction and can then apply certainnetwork policies in the SD-WAN to achieve better quality of service(QoS).

In particular, FIG. 7 illustrates an example system 700 for dynamicpolicy implementation for application-aware routing based on granularbusiness insights according to one or more embodiments herein. As shown,there are several customer workstations 710 (e.g., hospital locations).Assume, for example, that a user sends a page or emergency data todoctors, and the doctors can access this data via a web application 722hosted on their data center 720. The illustrative San Franciscoworkstation is instrumented by the application intelligence platform'sEUM agent 712, which captures critical business transactions 705. Thisdata is then sent to the application intelligence platform 730 (e.g.,with a corresponding controller 732, events service 734, and EUMcomponent 736).

The Web Application 722 is instrumented by the Application-Aware RoutingExtension 742 (e.g., a portion of the application intelligence platform730 implemented within the customer data center 720), which pulls thisdata from the application intelligence platform and evaluates configuredbusiness rules via business intelligence and critical event evaluationcomponent 744. Once a critical event is found (e.g., logging into acritical application), the extension communicates with the SD-WANcontroller 750, which in turn switches all traffic (e.g., via networkdevices 755, such as routers, switches, etc.) between the workstationand data center to a better (e.g., faster) channel across the internetservice provider 760 (e.g., from the standard channel 762 to the MPLSchannel 764), thereby using Business Intelligence to manipulate networktraffic. A future event (e.g., logging out of the critical application)would then cancel the use of the faster (or otherwise “better”) channel,accordingly.

Various types of business intelligence policies may be defined (e.g.,statically by a user or dynamically based on various machine learning orartificial intelligence algorithms). For example, individual businessfeatures (e.g., a first type of BT versus a second or third type of BT)may be associated with different IP-based routing policies (e.g.,routing the first type of BT through a better channel than the secondtype, and the second type better than the third type, and so on). Anybusiness feature policy may be established, and the associated IPaddress of the application/device participating in that business featuremay be extracted and managed at the IP-level according to the techniquesherein, accordingly.

FIG. 8 illustrates another example system 800 for dynamic policyimplementation for application-aware routing based on granular businessinsights. Namely, a user's mobile application 810 may be monitored(application performance monitoring 820 consuming application data 825),where again SD-WAN policies 830 may be implemented based on correlatingapplication/business transaction triggers to the user's IP address forimplementing the IP-based policies 835. In this manner, proactiveactions can be taken to provide better customer experiences,particularly impacting critical applications and business transactionsaccording to the techniques herein.

According to one or more embodiments of the techniques herein, theapplication-aware routing extension is capable of the followingfeatures, particularly for each specific browser-based application thatis monitored with a BRUM/EUM. First, the techniques herein can detecteach unique browser client request that makes a successful login requestand subsequent log out request, based on the browser client IP Addressand the URL pattern of the login and log out request. In addition, thetechniques herein can detect each unique browser client thatparticipates in “Enable Business Transaction” (EnableBT) (e.g.,login-BT) and subsequent “Disable Business Transaction” (DisableBT)(e.g., logout-BT) using browser client IP Address). Furthermore, thetechniques herein may send a JSON (option to send XML) record overHTTP/HTTPS for each unique successful browser client login request(e.g., EnableBT request) and subsequent log out request (e.g., DisableBTrequest), to a configured REST endpoint. Note that the external RESTendpoint receiving the JSON/XML record may take the browser client IPAddress (included with other data in the JSON/XML record) and whenassociated with a login request (e.g., EnableBT), route the futurerequests for that IP Address to a different network, presumably withhigher throughput, and then upon receipt of a log out JSON/HTML record(e.g., DisableBT) for the same IP Address, switch the same IP Addressback to the prior network route (hence, “Business Transaction AwareRouting”).

According to the techniques herein, the extension should not sendduplicate records (e.g., make REST API calls for duplicate records) fora unique IP Address for the same request type (e.g., the same BT type),only one record when a unique IP Address makes a login request (e.g.,EnableBT request) and only one record when a unique IP Address makes alog out request (i.e. the extension must determine and track thebeginning and end of a session for each unique IP Address). Also, theextension should send only one JSON/XML record in each HTTP/HTTPSrequest to the third party REST endpoint.

Also, according to the techniques herein, the routing extension maycause the application intelligence platform Machine Agent to run andread its configuration from a monitor.xml file (though the code could bemigrated to work outside the machine agent), and may not require theMachine Agent to be associated with any other application intelligenceplatform component. (In one embodiment, the extension may also maintaina config.yaml file, within which may reside configurations related tocontrollers, event services, etc.) Furthermore, according to thetechniques herein, the application-aware routing extension may beconfigured (e.g., defined in a corresponding monitor.xml file) such thatthe browser based application is instrumented with the applicationintelligence platform Browser EUM JavaScript agent and is reporting datato the EUM Server, and that the “Store IP Address” setting is set totrue within the configuration for the same browser application (BrowserRequest IP Address Storage)—optionally via APIs during startup. Inaddition, the configuration may be set such that the same browserapplication has the application intelligence platform Browser EUMAnalytics enabled and is reporting data to the Events Service—optionallyvia APIs during startup, and further such that the applicationintelligence platform Machine Agent running the extension can connect tothe appropriate Events Service and to the third party REST endpoint.Note that a configurable URL for both the login and log out requestshould be configured to be unique enough to mark the beginning and endof a user's browser application session.

As shown in FIG. 9, for example, an illustrative system 900 herein(network router extension 920) (1) queries the browser_records schema inthe events service 910 periodically (e.g., once a minute) with the EUMapp key and events service API key to find new IP addresses that havetriggered an event (e.g., logged in or out). Next (2), the query resultsof IP addresses are checked and compared against the cache 925,identifying IP addresses to send to third party REST API 930. At thattime (3), new IP addresses that are associated with a triggered event(e.g., that have logged in and/or logged out) are sent to the third partREST API over HTTP/HTTPS. Then (4), the system updates the cache 925 toaccount for the new IP addresses sent to third party REST API 930.

Said differently, to obtain an IP address that corresponds to aparticular business transaction/feature trigger, the techniques hereinmay use a javascript agent associated with a browser Real UserMonitoring (BRUM/EUM) process to extract an end host's IP address, andmay send that IP address to event services of the applicationintelligence platform (along with the business feature/trigger).Periodically (e.g., every second or few seconds), the extension hereinlooks at the business features (e.g., BTID) for rules-based triggers,and then sends the associated IP addresses to the SD-WAN managementcontroller for implementation of one or more network policies. Inparticular, according to the techniques herein, the application-awarerouting extension prevents resending the same IP address again to theSD-WAN management until a change is needed in the implemented policies(e.g., a log off event or other trigger). This is made possible throughstate management (e.g., state machines) within the application-awarerouting extension process to maintain the state of each shared IPaddress, including when failures or outages occur, such that only inresponse to a triggered state change do the IP addresses get shared withthe SD-WAN controller.

FIG. 10A illustrates an example graph 1000 of monitored traffic ratesover time based on the techniques herein being implemented. Forinstance, the “triangle” line 1010 (shown as GigabitEthernet4) plots theusage of a standard channel (receive/Rx 1012 and transmit/Tx 1014),e.g., for traffic not accessing critical data (e.g., critical patients).Assume, however, that at time “A” a business intelligence trigger isdetected (e.g., a specific log in activity, such as a doctor logginginto a critical patient's account), causing implementation of a givenapplication-aware policy. As such, the “circle” line 1020 (shown asGigabitEthernet2), indicative of a critical channel usage (e.g., an MPLSchannel), begins to show increased traffic flow (e.g., for bothtransmit/Tx 1024 and receive/Rx 1022). As shown in FIG. 10B, on theother hand, another trigger may be detected at time “B” (e.g., a log offevent) that results in the critical traffic on critical channel beingreduced over time based on the changed policy. (Notably, the changes maybe immediate, gradual, and so on.)

According to the techniques herein, the application-aware routingextension provides more context about business-related features toSD-WAN management, particularly by correlating those business-relatedfeatures to IP addresses that can have network policies applied thereto,based on user-defined policies and rules. The rules themselves can bevery flexible, where business intelligence features (e.g., businesstransaction or BTIDs) can be used to define policies that until now hadnot been possible. That is, the techniques herein provide forIP-address-based routing in an SD-WAN (managed in an IP space) that istriggered by BT-based policies (managed in an application intelligencespace).

In closing, FIG. 11 illustrates an example simplified procedure fordynamic policy implementation for application-aware routing based ongranular business insights in accordance with one or more embodimentsdescribed herein. For example, a non-generic, specifically configureddevice (e.g., device 200, particularly an application intelligenceplatform device) may perform procedure 1100 by executing storedinstructions (e.g., process 248, such as an application aware routingprocess). The procedure 1100 may start at step 1105, and continues tostep 1110, where, as described in greater detail above, one or morefeatures of an initiated application transaction within an application(e.g., a log-in/on event) are captured (e.g., by monitoring theapplication through one or more user application monitoring agents). Forexample, the one or more features may comprise a transaction type, aBTID, an application identifier, a user identifier, a user groupidentifier, and so on. In step 1115, the process may then apply the oneor more features to one or more application-based policies to determine,in step 1120, whether a policy trigger exists for the initiatedapplication transaction based on applying the one or more features tothe one or more application-based policies. For instance, theapplication-based policies may correspond to setting different levels ofpriority, different QoS, and so on based on the features.

In step 1125, in response to determining the policy trigger for theinitiated application transaction, the process then obtains a networkaddress associated with the application (e.g., extracting the networkaddress by converting a string value from an events service associatedwith the application into an Internet Protocol (IP) address). Inaddition, in step 1130, the process maps the particular policy triggerfrom the one or more application-based policies to one or morecorresponding network-based policies. For instance, when the policytrigger for the initiated application transaction comprisesapplication-based priority, then mapping the particular policy triggerfrom the one or more application-based policies to the one or morecorresponding network-based policies may comprise mapping theapplication-based priority to a corresponding network-based priority.Note also that as described above, the one or more correspondingnetwork-based policies may be created by converting one or more criteriaof the one or more application-based policies into one or more numericnetwork metrics for the one or more corresponding network-basedpolicies.

In step 1135, the process can now instruct a network controller (e.g.,SD-WAN controller) to apply the one or more corresponding network-basedpolicies to the network address associated with the application, causingthe network controller to configure a computer network to manage networktraffic associated with the network address according to the one or morecorresponding network-based policies. Note that in one embodiment, thenetwork controller may also be instructed of the one or morecorresponding network-based policies to apply to the network address(e.g., informing the controller of exactly what the policy ison-the-fly), while in another embodiment, the network controller may beinstructed to apply one or more pre-configured correspondingnetwork-based policies to the network address.

According to further embodiments of the techniques herein, in step 1140the process may prevent duplicate instructions to the network controllerto apply network-based policies to the network address, as describedabove.

Upon determining an end to the initiated application transaction in step1145, then in step 1150, in response to the end of the initiatedapplication transaction, the process may instruct the network controllerto cease application of the one or more corresponding network-basedpolicies to the network address associated with the application (e.g., alog-off/out event).

The simplified procedure 1100 may then end in step 1155, notably withthe ability to continue capturing application features and applyingpolicies, accordingly. Other steps may also be included generally withinprocedure 1100.

It should be noted that while certain steps within procedure 1100 may beoptional as described above, the steps shown in FIG. 11 are merelyexamples for illustration, and certain other steps may be included orexcluded as desired. Further, while a particular order of the steps isshown, this ordering is merely illustrative, and any suitablearrangement of the steps may be utilized without departing from thescope of the embodiments herein.

The techniques described herein, therefore, provide for dynamic policyimplementation for application-aware routing based on granular businessinsights. In particular, the techniques herein provide fordifferentiated managed SD-WAN services for Internet service providers(ISPs) that are more intelligent than standard SD-WAN management. Forinstance, an ISP can now provide the application integration servicesdescribed above to customers in order to give customer-defined criticalapplication traffic a better treatment through the network, resulting ina better overall user experience. Customers, on the other hand, can nowhave finer-grained control over application-based policies that can beeasily changed and applied, and implemented on-demand based on changingtraffic conditions and/or triggers. Note further that the techniquesherein can also provide for AIOPS (Artificial Intelligence for ITOperations) use cases, such as, for example, responding to a networkfailure with automatically applying network policies to route criticalbusiness transactions through a 4G LTE channel.

Notably, there are many application-aware network use cases that mayadvantageously make use of the techniques herein. For example, criticalusers/groups of users (e.g., Platinum/Gold Customers, customers atpremium lounge kiosks at airports/hotels, etc.) may receive proactivelyprovided higher QoS to their traffic based on baselines for criticalusers (e.g., granular control on users on a per location and applicationfor key users). Also, critical applications/business transactions (e.g.,high dollar value trades from a bank branch, total orders and averageorder size trends, conversion rate on sale days, end of day productiondata upload on oil rigs, and so on) may obtain value from the techniquesherein due to further cost reduction on top of SD-WAN solutions bypredictive business metrics driven automated network configuration(e.g., working to reduce bottlenecks before they occur or resolving themquickly for key transactions and applications). Business events/metrics,too (e.g., average hourly transaction processing time for a store andcustomer critical transactions, jumbo loan processing time for bankbranches, average hourly order size trends on new product sales perbranch, and so on) may now be used for granular and predictive networkchanges led by business level metrics providing highly flexible solution(i.e., automated policy driven network changes). Lastly, value isprovided for customer end points (e.g., predictable device performancefor key devices such as kiosks on oil-rigs or IOT sensors on fieldsites, etc.) in that device-by-device and app-level data for real-timeapp behavior impact provides better service level (SL) management at thenetwork level.

In still further embodiments of the techniques herein, a business impactof dynamic policy implementation for application-aware routing based ongranular business insights can also be quantified. That is, because ofissues related to specific applications/processes (e.g., lost traffic,slower servers, overloaded network links, etc.) affecting networkmetrics, and vise versa, various corresponding business transactions mayhave been correspondingly affected for those applications/processes(e.g., online purchases were delayed, page visits were halted beforefully loading, user satisfaction or dwell time decreased, etc.), whileother processes (e.g., on other network segments or at other times)remain unaffected. The techniques herein, therefore, can correlate theeffects of dynamic policy implementation for application-aware routingbased on granular business insights with various business transactionsin order to better understand the affect such implementation may havehad on the business transactions, accordingly.

Illustratively, the techniques described herein may be performed byhardware, software, and/or firmware, such as in accordance with theillustrative application-aware routing (e.g., extension) process 248,which may include computer executable instructions executed by theprocessor 220 to perform functions relating to the techniques describedherein, e.g., in conjunction with corresponding processes of otherdevices in the computer network as described herein (e.g., on networkagents, controllers, computing devices, servers, etc.). Notably, theextension is configured to work when the application intelligenceplatform controller, EUM Server, and Events Service is deployedon-premise or in an application intelligence platform SaaS environment.

According to the embodiments herein, a method herein may comprise:capturing, by a process, one or more features of an initiatedapplication transaction within an application; applying, by the process,the one or more features to one or more application-based policies;determining, by the process, a policy trigger for the initiatedapplication transaction based on applying the one or more features tothe one or more application-based policies; obtaining, by the process inresponse to determining the policy trigger for the initiated applicationtransaction, a network address associated with the application; mapping,by the process, the particular policy trigger from the one or moreapplication-based policies to one or more corresponding network-basedpolicies; and instructing, by the process, a network controller to applythe one or more corresponding network-based policies to the networkaddress associated with the application, causing the network controllerto configure a computer network to manage network traffic associatedwith the network address according to the one or more correspondingnetwork-based policies.

In one embodiment, the network controller comprises a software-definedwide area network (SD-WAN) controller. In one embodiment, the one ormore features comprise a transaction type. In one embodiment, the policytrigger for the initiated application transaction comprisesapplication-based priority, and wherein mapping the particular policytrigger from the one or more application-based policies to the one ormore corresponding network-based policies comprises mapping theapplication-based priority to a corresponding network-based priority. Inone embodiment, the method further comprises preventing duplicateinstructions to the network controller to apply network-based policiesto the network address. In one embodiment, the method further comprisesdetermining an end to the initiated application transaction, andinstructing, in response to the end of the initiated applicationtransaction, the network controller to cease application of the one ormore corresponding network-based policies to the network addressassociated with the application. In one embodiment, the method furthercomprises instructing the network controller of the one or morecorresponding network-based policies to apply to the network address. Inone embodiment, the method further comprises instructing the networkcontroller to apply one or more pre-configured correspondingnetwork-based policies to the network address. In one embodiment,obtaining the network address comprises extracting the network addressby converting a string value from an events service associated with theapplication into an Internet Protocol (IP) address. In one embodiment,the method further comprises creating the one or more correspondingnetwork-based policies by converting one or more criteria of the one ormore application-based policies into one or more numeric network metricsfor the one or more corresponding network-based policies. In oneembodiment, the method further comprises monitoring the applicationthrough one or more user application monitoring agents.

According to the embodiments herein, a tangible, non-transitory,computer-readable medium herein may have computer-executableinstructions stored thereon that, when executed by a processor on acomputer, may cause the computer to perform a method comprising:capturing one or more features of an initiated application transactionwithin an application; applying the one or more features to one or moreapplication-based policies; determining a policy trigger for theinitiated application transaction based on applying the one or morefeatures to the one or more application-based policies; obtaining, inresponse to determining the policy trigger for the initiated applicationtransaction, a network address associated with the application; mappingthe particular policy trigger from the one or more application-basedpolicies to one or more corresponding network-based policies; andinstructing a network controller to apply the one or more correspondingnetwork-based policies to the network address associated with theapplication, causing the network controller to configure a computernetwork to manage network traffic associated with the network addressaccording to the one or more corresponding network-based policies.

Further, according to the embodiments herein an apparatus herein maycomprise: one or more network interfaces to communicate with a network;a processor coupled to the network interfaces and configured to executeone or more processes; and a memory configured to store a processexecutable by the processor, the process, when executed, configured to:capture one or more features of an initiated application transactionwithin an application; apply the one or more features to one or moreapplication-based policies; determine a policy trigger for the initiatedapplication transaction based on applying the one or more features tothe one or more application-based policies; obtain, in response todetermining the policy trigger for the initiated applicationtransaction, a network address associated with the application; map theparticular policy trigger from the one or more application-basedpolicies to one or more corresponding network-based policies; andinstruct a network controller to apply the one or more correspondingnetwork-based policies to the network address associated with theapplication, causing the network controller to configure a computernetwork to manage network traffic associated with the network addressaccording to the one or more corresponding network-based policies.

While there have been shown and described illustrative embodimentsabove, it is to be understood that various other adaptations andmodifications may be made within the scope of the embodiments herein.For example, while certain embodiments are described herein with respectto certain types of networks in particular, the techniques are notlimited as such and may be used with any computer network, generally, inother embodiments. Moreover, while specific technologies, protocols, andassociated devices have been shown, such as Java, TCP, IP, and so on,other suitable technologies, protocols, and associated devices may beused in accordance with the techniques described above. In addition,while certain devices are shown, and with certain functionality beingperformed on certain devices, other suitable devices and processlocations may be used, accordingly. That is, the embodiments have beenshown and described herein with relation to specific networkconfigurations (orientations, topologies, protocols, terminology,processing locations, etc.). However, the embodiments in their broadersense are not as limited, and may, in fact, be used with other types ofnetworks, protocols, and configurations.

Moreover, while the present disclosure contains many other specifics,these should not be construed as limitations on the scope of anyembodiment or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularembodiments. Certain features that are described in this document in thecontext of separate embodiments can also be implemented in combinationin a single embodiment. Conversely, various features that are describedin the context of a single embodiment can also be implemented inmultiple embodiments separately or in any suitable sub-combination.Further, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

For instance, while certain aspects of the present disclosure aredescribed in terms of being performed “by a server” or “by acontroller”, those skilled in the art will appreciate that agents of theapplication intelligence platform (e.g., application agents, networkagents, language agents, etc.) may be considered to be extensions of theserver (or controller) operation, and as such, any process stepperformed “by a server” need not be limited to local processing on aspecific server device, unless otherwise specifically noted as such.Furthermore, while certain aspects are described as being performed “byan agent” or by particular types of agents (e.g., application agents,network agents, etc.), the techniques may be generally applied to anysuitable software/hardware configuration (libraries, modules, etc.) aspart of an apparatus or otherwise.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in the present disclosure should not be understoodas requiring such separation in all embodiments.

The foregoing description has been directed to specific embodiments. Itwill be apparent, however, that other variations and modifications maybe made to the described embodiments, with the attainment of some or allof their advantages. For instance, it is expressly contemplated that thecomponents and/or elements described herein can be implemented assoftware being stored on a tangible (non-transitory) computer-readablemedium (e.g., disks/CDs/RAM/EEPROM/etc.) having program instructionsexecuting on a computer, hardware, firmware, or a combination thereof.Accordingly, this description is to be taken only by way of example andnot to otherwise limit the scope of the embodiments herein. Therefore,it is the object of the appended claims to cover all such variations andmodifications as come within the true intent and scope of theembodiments herein.

What is claimed is:
 1. A method, comprising: capturing, by a process, abusiness transaction associated with an application; determining, by theprocess, one or more application-based policies associated with a typeof the business transaction; determining, by the process, anapplication-based priority for the business transaction based on the oneor more application-based policies; obtaining, by the process inresponse to determining the application-based priority, an InternetProtocol (IP) address associated with the application; mapping, by theprocess, the application-based priority to a corresponding network-basedpriority different from the application-based priority; and instructing,by the process, a network controller to apply the correspondingnetwork-based priority to the IP address associated with theapplication, causing the network controller to configure a computernetwork to manage network traffic associated with the IP addressaccording to the corresponding network-based priority, wherein thecorresponding network-based priority is created by converting one ormore criteria of the one or more application-based policies into one ormore numeric network metrics for the corresponding network-basedpriority.
 2. The method as in claim 1, wherein the network controllercomprises a software-defined wide area network (SD-WAN) controller. 3.The method as in claim 1, further comprising: preventing duplicateinstructions to the network controller to apply network-based prioritiesto the IP address.
 4. The method as in claim 1, further comprising:determining an end to the business transaction; and instructing, inresponse to the end of the business transaction, the network controllerto cease the application of the corresponding network-based priority tothe IP address associated with the application.
 5. The method as inclaim 1, further comprising: instructing the network controller to applyone or more pre-configured corresponding network-based policies to theIP address.
 6. The method as in claim 1, further comprising: monitoringthe application through one or more user application monitoring agents.7. A tangible, non-transitory, computer-readable medium havingcomputer-executable instructions stored thereon that, when executed by aprocessor on a computer, cause the computer to perform a methodcomprising: capturing a business transaction associated with anapplication; determining one or more application-based policiesassociated with a type of the business transaction; determining anapplication-based priority for the business transaction based on the oneor more application-based policies; obtaining, in response todetermining the application-based priority, an Internet Protocol (IP)address associated with the application; mapping the application-basedpriority to a corresponding network-based priority different from theapplication-based priority; and instructing a network controller toapply the corresponding network-based priority to the IP addressassociated with the application, causing the network controller toconfigure a computer network to manage network traffic associated withthe IP address according to the corresponding network-based priority,wherein the corresponding network-based priority is created byconverting one or more criteria of the one or more application-basedpolicies into one or more numeric network metrics for the correspondingnetwork-based priority.
 8. The computer-readable medium as in claim 7,wherein the network controller comprises a software-defined wide areanetwork (SD-WAN) controller.
 9. The computer-readable medium as in claim7, wherein the method further comprises: preventing duplicateinstructions to the network controller to apply network-based prioritiesto the IP address.
 10. The computer-readable medium as in claim 7,wherein the method further comprises: determining an end to the businesstransaction; and instructing, in response to the end of the businesstransaction, the network controller to cease the application of thecorresponding network-based priority to the IP address associated withthe application.
 11. The computer-readable medium as in claim 7, whereinthe method further comprises: instructing the network controller toapply one or more pre-configured corresponding network-based policies tothe IP address.
 12. An apparatus, comprising: one or more networkinterfaces to communicate with a network; a processor coupled to thenetwork interfaces and configured to execute one or more processes; anda memory configured to store a process executable by the processor, theprocess, when executed, configured to: capture a business transactionassociated with an application; determine one or more application-basedpolicies associated with a type of the business transaction; determinean application-based priority for the business transaction based on theone or more application-based policies; obtain, in response todetermining the application-based priority, an Internet Protocol (IP)address associated with the application; map the application-basedpriority to a corresponding network-based priority different from theapplication-based priority; and instruct a network controller to applythe corresponding network-based priority to the IP address associatedwith the application, causing the network controller to configure acomputer network to manage network traffic associated with the IPaddress according to the corresponding network-based priority, whereinthe corresponding network-based priority is created by converting one ormore criteria of the one or more application-based policies into one ormore numeric network metrics for the corresponding network-basedpriority.